• International Journal of Automotive Technology
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• v.8 no.2
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• pp.203-209
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• 2007

As the vehicle electronic control technology quickly grows and becomes more sophisticated, a more efficient means than the traditional in-vehicle driving test is required for the design, testing, and tuning of electronic control units (ECU). For this purpose, the hardware-in-the-loop simulation (HILS) scheme is very promising, since significant portions of actual driving test procedures can be replaced by HIL simulation. The HILS incorporates hardware components in the numerical simulation environment, and this yields results with better credibility than pure numerical simulations can offer. In this study, a HILS system has been developed for ESP (Electronic Stability Program) ECUs. The system consists of the hardware component, which that includes the hydraulic brake mechanism and an ESP ECU, the software component, which virtually implements vehicle dynamics with visualization, and the interface component, which links these two parts together. The validity of HIL simulation is largely contingent upon the accuracy of the vehicle model. To account for this, the HILS system in this research used the commercial software CarSim to generate a detailed full vehicle model, and its parameters were set by using design data, SPMD (Suspension Parameter Measurement Device) data, and data from actual vehicle tests. Using the developed HILS system, performance of a commercial ESP ECU was evaluated for a virtual vehicle under various driving conditions. This HILS system, with its reliability, will be used in various applications that include durability testing, benchmarking and comparison of commercial ECUs, and detection of fault and malfunction of ESP ECUs.

• Earthquakes and Structures
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• v.17 no.2
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• pp.143-162
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• 2019

Motivated by a simpler and more compact hybrid active tuned mass damper (ATMD) system with wide frequency spacing (i.e., high robustness) but not reducing the effectiveness using the least number of ATMD units, the active tuned tandem mass dampers (ATTMD) have been proposed to attenuate undesirable oscillations of structures under the ground acceleration. Likewise, it is expected that the frequency spacing of the ATTMD is comparable to that of the active multiple tuned mass dampers (AMTMD) or the multiple tuned mass dampers (MTMD). In accordance with the mode generalised system in the specific vibration mode being controlled (simply referred herein to as the structure), the closed-form expression of the dimensionless displacement variances has been derived for the structure with the attached ATTMD. The criterion for the optimum searching may then be determined as minimization of the dimensionless displacement variances. Employing the gradient-based optimization technique, the effects of varying key parameters on the performance of the ATTMD have been scrutinized in order to probe into its superiority. Meanwhile, for the purpose of a systematic comparison, the optimum results of two active tuned mass dampers (two ATMDs), two tuned mass dampers (two TMDs) without the linking damper, and the TTMD are included into consideration. Subsequent to work in the frequency domain, a real-time Simulink implementation of dynamic analysis of the structure with the ATTMD under earthquakes is carried out to verify the findings of effectiveness and stroke in the frequency domain. Results clearly show that the findings in the time domain support the ones in the frequency domain. The whole work demonstrates that ATTMD outperforms two ATMDs, two TMDs, and TTMD. Thereinto, a wide frequency spacing feature of the ATTMD is its highlight, thus deeming it a high robustness control device. Furthermore, the ATTMD system only needs the linking dashpot, thus embodying its simplicity.

• Journal of odor and indoor environment
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• v.17 no.4
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• pp.372-380
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• 2018

To abate the problem of odor from restaurants, a hybrid adsorbent consisting of organic and inorganic materials was developed and evaluated using acetaldehyde as a model compound was deveioped and evaluated. Powders of activated carbon, bentonite, and calcium hydroxide were mixed and calcinated to form adsorbent structure. The surface area of the hybrid adsorbent was smaller than that of high-quality activated carbon, but its microscopic image showed that contours and pores were developed on its surface. To determine its adsorption capacity, both batch isotherm and continuous flow column experiments were performed, and these results were compared with those using commercially available activated carbon. The isotherm tests showed that the hybrid adsorbent had a capacity 40 times higher than that of the activated carbon. In addition, the column experiments revealed that breakthrough time of the hybrid adsorbent was 2.5 times longer than that of the activated carbon. These experimental results were fitted to numerical simulations by using a homogeneous surface diffusion model (HSDM); the model estimated that the hybrid adsorbent might be able to remove acetaldehyde at a concentration of 40 ppm for a 5-month period. Since various odor compounds are commonly emitted as a mixture when meat is barbecued, it is necessary to conduct a series of experiments and HSDM simulations under various conditions to obtain design parameters for a full-scale device using the hybrid adsorbent.

• Journal of Biosystems Engineering
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• v.43 no.4
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• pp.426-439
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• 2018

Purpose: To continuously monitor soil and climatic properties, a data acquisition system (DAQ) was developed and tested in plum farms (Gyewol-ri and Haechang-ri, Suncheon, Korea). Methods: The DAQ consisted of a Raspberry-Pi processor, a modem, and an ADC board with multiple sensors (soil moisture content (SEN0193), soil temperature (DS18B20), climatic temperature and humidity (DHT22), and rainfall gauge (TR-525M)). In the laboratory, various tests were conducted to calibrate SEN0193 at different soil moistures, soil temperatures, depths, and bulk densities. For performance comparison of the SEN0193 sensor, two commercial moisture sensors (SMS-BTA and WT-1000B) were tested in the field. The collected field data in Raspberry-Pi were transmitted and stored on a web server database through a commercial communications wireless network. Results: In laboratory tests, it was found that the SEN0193 sensor voltage reading increased significantly with an increase in soil bulk density. A linear calibration equation was developed between voltage and soil moisture content depending on the farm soil bulk density. In field tests, the SEN0193 sensor showed linearity (R = 0.76 and 0.73) between output voltage and moisture content; however, the other two sensors showed no linearity, indicating that site-specific calibration is important for accurate sensing. In the long-term monitoring results, it was observed that the measured climate temperature was almost the same as website information. Soil temperature information was higher than the values measured by DS18B20 during spring and summer. However, the local rainfall measured using TR 525M was significantly different from the values on the website. Conclusion: Based on the test results obtained using the developed monitoring system, it is thought that the measurement of various parameters using one device would be helpful in monitoring plum growth. Field data from the local farm monitoring system can be coupled with website information from the weather station and used more efficiently.

• Journal of Astronomy and Space Sciences
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• v.38 no.4
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• pp.237-250
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• 2021

A rover is a planetary surface exploration device designed to move across the ground on a planet or a planetary-like body. Exploration rovers are increasingly becoming a vital part of the search for scientific evidence and discoveries on a planetary satellite of the Sun, such as the Moon or Mars. Reliable behavior and predictable locomotion of a rover is important. Understanding soil behavior and its interaction with rover wheels-the terramechanics-is of great importance in rover exploration performance. Up to now, many researchers have adopted Bekker's semiempirical model to predict rover wheelsoil interaction, which is based on the assumption that soil is deformable when a pressure is applied to it. Despite this basic assumption of the model, the pressure-sinkage relation is not fully understood, and it continues to present challenges for rover designers. This article presents a new pressure-sinkage model based on dimensional analysis (DA) and results of bevameter tests. DA was applied to the test results in order to propose a new pressure-sinkage model by reducing physical quantitative parameters. As part of the work, a new bevameter was designed and built so that it could be successfully used to obtain a proper pressure-sinkage relation of Korean Lunar Soil Simulant (KLS-1). The new pressure-sinkage model was constructed by using three different sizes of flat plate diameters of the bevameter. The newly proposed model was compared successfully with other models for validation purposes.

• Advances in nano research
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• v.13 no.2
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• pp.199-206
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• 2022

We present the high-brightness large-area 10.1" in-cell polarizer display panel integrated with a wire grid polarizer (WGP) and metal reflector, from the initial design to final system development in a commercially feasible level. We have modeled and developed the WGP architecture integrated with the metal reflector in a single in-cell layer, to achieve excellent polarization efficiency as well as brightness enhancement through the light recycling effect. After the optimization of key experimental parameters via Taguchi method, the roll nanoimprint lithography employing a flexible large-area tiled mold has been utilized to create the 90 nm-pitch polymer resist pattern with the 54.1 nm linewidth and 5.1 nm residual layer thickness. The 90 nm-pitch Al gratings with the 51.4 nm linewidth and 2150 Å height have been successfully fabricated after subsequent etch process, providing the in-cell WGPs with high optical performance in the entire visible light regime. Finally we have integrated the WGP in a commercial 10.1" display device and demonstrated its actual operation, exhibiting 1.24 times enhancement of brightness compared to a conventional film polarizer-based one, with the contrast ratio of 1,004:1. Polarization efficiency and transmittance of the developed WGPs in an in-cell polarizer panel achieve 99.995 % and 42.3 %, respectively.

• Journal of the Microelectronics and Packaging Society
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• v.29 no.4
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• pp.55-61
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• 2022

There is a major interest in diagnostic technology for multiple cancers worldwide. In order to reduce the difficulty of cancer diagnosis, a liquid biopsy technology based on a microfluidic device using trace amounts of biofluids such as blood is being studied. And optical biosensing, which measures the concentration of analytes through fluorescence imaging using biofluids, requires various strategies to improve sensitivity, and specialists and equipment are needed to carry out these strategies. This leads to an increase in diagnostic and production costs, and it is necessary to develop a technology to solve this problem. In this paper, we design and propose a fluorescent multi-cancer diagnostic sensing platform structure that implements passive self-separation technology and molecular recognition activation functions by fluid mixing, only with the geometry and microfluidic phenomena of microchannels based on self-driven flow by capillary force. In order to check the parameters affecting the performance of the plasma separation part of the designed sensor, the hydrodynamic diameter of the channel and the viscosity of the fluid were set as variables to confirm the formation of plasma separation flow through simulation. And finally, we propose an optimal sensor platform structure.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.6
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• pp.1353-1362
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• 2023

Various methods are being attempted to resolve the inconvenience of blood glucose meters used to check blood sugar levels. In this paper, we attempted to estimate blood sugar levels non-invasively using machine learning technology from spectral data acquired using a near-infrared sensor. The non-invasive blood glucose meter used in the study has a total of six near-infrared ray emitters, including visible rays, and a light receiver that receives them. It is a device created to collect spectral data on specific parts of the human body, such as the fingers. To verify whether there was a significant difference depending on blood sugar level, we attempted to estimate blood sugar level through machine learning algorithms. As a result of applying five machine learning algorithm techniques to the collected data and adjusting various hyper parameters, it was confirmed that the support vector regression algorithm showed the best performance.

• Journal of the Korea Organic Resources Recycling Association
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• v.23 no.2
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• pp.47-52
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• 2015

A microbial fuel cell (MFC) is a device that can be obtained electricity from a variety of organic through the catalytic reaction of the microorganism. The MFC can be applied to various fields, and research is required to promote the performance of the microbial fuel cell for commercialization. The lower performance of an MFC is due to oxygen reduction at the cathode and the longer time of microbial degradation at anode. The MFC amount of power is sufficient but, in consideration of many factors, as a renewable energy, now commonly power density as compared to Nafion117 it is an ion exchange membrane used is PP (Poly Propylene) from 80 to about 11 fold higher, while reducing the cost to process wastewater is changed to a microporous non-woven fabric of a low cost, it may be energy-friendly environment to generate electricity. All waste, in that it can act as a bait for microorganisms, sustainability of the microbial fuel cell is limitless. The latest research on the optimization and performance of the operating parameters are surveyed and through the SSaM-GG(Smart, Shared, and Mutual- Green Growth) or GG-SSaM(Green Growth - Smart, Shared, and Mutual) as the concept of sustainable development in MFC, the middle indices are developed in this study.

• Journal of Intelligence and Information Systems
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• v.29 no.1
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• pp.107-119
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• 2023

The technology that recognizes a soldier's motion and movement status has recently attracted large attention as a combination of wearable technology and artificial intelligence, which is expected to upend the paradigm of troop management. The accuracy of state determination should be maintained at a high-end level to make sure of the expected vital functions both in a training situation; an evaluation and solution provision for each individual's motion, and in a combat situation; overall enhancement in managing troops. However, when input data is given as a timer series or sequence, existing feedforward networks would show overt limitations in maximizing classification performance. Since human behavior data (3-axis accelerations and 3-axis angular velocities) handled for military motion recognition requires the process of analyzing its time-dependent characteristics, this study proposes a high-performance data-driven classifier which utilizes the long-short term memory to identify the order dependence of acquired data, learning to classify eight representative military operations (Sitting, Standing, Walking, Running, Ascending, Descending, Low Crawl, and High Crawl). Since the accuracy is highly dependent on a network's learning conditions and variables, manual adjustment may neither be cost-effective nor guarantee optimal results during learning. Therefore, in this study, we optimized hyperparameters using Bayesian optimization for maximized generalization performance. As a result, the final architecture could reduce the error rate by 62.56% compared to the existing network with a similar number of learnable parameters, with the final accuracy of 98.39% for various military operations.